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Infrastructure for a better future

Infrastructure for a better future
Newsroom
4 hrs ago
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Editor’s note: The opinions in this article are the author’s, as published by our content partner, and do not represent the views of MSN or Microsoft.
New Zealanders have spoken. They want less congestion, cleaner water, cheaper housing, and a clear focus on climate change when it comes to urban planning. One body has the task to develop a direction to achieve this over the next 30 years. Can it do it? asks business editor Nikki Mandow
In 1807, the city officials of New York had a visionary idea: to design a layout for Manhattan Island which would cater for potential population growth for the next 50 years, maybe 100 years. ....

New York , United States , Manhattan Island , New Zealand , New York University , New Zealanders , Shlomo Angel , Wikimedia Commons , Grant Robertson , Ross Copland , John Sefton , Lynn Grieveson , Nikki Mandow , Geoff Cooper , York University Urban Expansion , Federal Reserve , Auckland Council , Zealand Infrastructure Commission , Commissioner Plan , New York City , New York Commissioner , Newsroom The New York Commissioner , New Zealand Infrastructure Commission , Newsroom Geoff Cooper , Infrastructure Strategy , Infrastructure Minister Grant Robertson ,

The Geography of COVID-19

NEW GEOGRAPHY-The ongoing pandemic is reshaping the geography of our planet, helping some areas, and hurting others.
In the West, the clear winners have been the sprawling suburbs and exurbs, while dense cores have been dealt a powerful blow. The pandemic also has accelerated class differences and inequality, with poor and working-class people around the world paying the dearest price.
These conclusions are based on data we have repeatedly updated. Despite some variations, our earlier conclusions hold up: the virus wreaked the most havoc in areas of high urban density. This first became evident in the alarming pre-lockdown fatalities that occurred in New York City and the suburban commuting shed from which many of the employees in the huge Manhattan business district are drawn. Similar patterns have been seen in Europe and Asia as well. ....

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Dünyayı mahvettik! Google'dan korkunç paylaşım!

Dünyayı mahvettik! Google'dan korkunç paylaşım!
teknolojioku.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from teknolojioku.com Daily Mail and Mail on Sunday newspapers.

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New Land Use Mapping Paints a Clearer Picture of Urban Life

Mapping land use in Mexico City and other urban areas can be a key tool to help cities manage their resources and improve quality of life. Photo by Nitin Badjatia/Unsplash
Remote sensing has revolutionized how we measure and understand the Earth. We can now track deforestation across the globe, predict end-of-season crop yields and identify wildfires in near real-time. But exploration into its possibilities for urban areas has only just begun. Conventional land cover maps, which categorize the surface of the Earth into groupings like “forest” or “water” or “tundra,” often lump urban areas into a single category, like “urban” or “built-up.” This is useful for mapping urban extent generally, but does not capture the complexity of urban areas. Mapping land ....

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Mapping Urban Land Use in India and Mexico using Remote Sensing and Machine Learning

This technical note describes the data sources and methodology underpinning a computer system for the automated generation of land use/land cover (LULC) maps of urban areas based on medium-resolution (10–30m/pixel) satellite imagery. The system and maps deploy the LULC taxonomy of the Atlas of Urban Expansion 2016 Edition: open, nonresidential, roads, and four types of residential space. We used supervised machine learning techniques to apply this taxonomy at scale. Distinguishing between recognizable, clearly defined types of land use within a built-up area, rather than merely delineating artificial land cover, enables a huge variety of potential applications for policy, planning, and research. We demonstrate the training and application of machine-learning-based algorithms to characterize LULC over a large spatial and temporal range in a way that avoids many of the onerous constraints and expenses of the traditional LULC mapping process: manual identification and classificatio ....

Urban Expansion , Spatial Characterization , Urban Land Use , Machine Learning , நகர்ப்புற விரிவாக்கம் , நகர்ப்புற நில பயன்பாடு , இயந்திரம் கற்றல் ,